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The multi-objective control problem for discrete bilinear system with disturbances is studied and a multi-objective optimal control algorithm for solving discrete bilinear systems with sinusoidal disturbances is proposed. In the lower order of the algorithm, the auxiliary Lagrangian problem of bilinear -two quadratic form structure is solved by Dynamic Programming. The weighting vector in the auxiliary...
In this paper, a High Precise Optimization Algorithm for manipulating multi-layered feed-forward neural network is studied. Its basic principle is: defining neural network average error as objective function, weights and thresholds as design variables, through design variables rationally sorted, objective function is dynamically formed. Compared the new method with BP, the optimum step-length can...
Speeding of E-commerce and Internet nowadays promote development, reform and recombination of logistics industry. More and more professionals focus here and approve concept of 4PL, which is the integrator of logistics industry, owns obvious advantages, and can play a role in today's highly competitive condition. In this paper, a multi-objective and multi-task routing problem of 4PL is considered,...
When solving complex function optimization problem, Differential evolution(DE) algorithms may suffer from low convergence rate. In this paper, we propose an improved differential evolution algorithm named n-IDE. Our algorithm uses Gaussian sequence to dynamically generate zoom factors and applies an improved hybrid mutation strategy to individuals in order to improve the overall performance. We compare...
In this paper, dynamic role assignment and collision avoidance based on consensus tracking algorithm are investigated for systems with complete communication graph. First, based on the traditional consensus protocol, consensus-based control algorithm with dynamic role assignment is proposed. To make each agent reach the closest formation point, we give an efficient assignment solution by solving an...
Photovoltaic grid-connected inverter system has the advantages of simple topology and low cost. Since the output power of photovoltaic devices is a nonlinear function of the external environment load, to maximize the performance of photovoltaic devices, Maximum Power Point Tracking (MPPT) control should adjust the duty cycle disturbance based on the work of photovoltaic devices. Although MPPT control...
According to the flight path planning problem in dynamic environment, this paper gives a method of analysis. First, the radar threat field based on Voronoi diagram is created, and the track performance indicators established based on radar threat cost and fuel cost. Then the dijkstra algorithm was improved, and the algorithm is used for path planning in dynamic environment‥ Finally, the simulation...
This paper introduces the implementation process of intelligent vehicle path planning, including the establishment of environmental models, path search algorithm, as well as the visualization of digital map. Firstly, the article introduces the path planning and several algorithms; secondly, the A * algorithm is described, as well as the representation of environment model; thirdly, the article introduces...
The generalized predictive control is applied to the industrial arc furnace electrode regulator system. The detailed design procedure of the generalized predictive controller is presented. Based on multi-step prediction, rolling optimization and online correction, the optimal control law is obtained. The results of simulation show that this proposed algorithm can restrain arc disturbance effectively,...
Due to the closeness between theory and industrial practice, the scheduling problem has been investigated by many experts and practitioners. The mode of continuous casting and hot charge rolling in the steel making is one of the important research areas. Limited buffers and due dates of jobs which characterize the problem here investigated. Based on the analysis from a new angle, a hybrid algorithm,...
Job shop scheduling has been an active area of research for several decades. However, there seems to have been a significant gap between the theoretical research in academia and practical application in industry. The scheduling system, which are developed aiming at the vast library of benchmark problems, usually faces some challenges when applying in the real manufacturing environment to support the...
With the development of intelligent algorithm, GA and PSO have become the hot spot for the study on multi-objective optimization in recently years. Information sharing is the core of PSO algorithm, Comparing with GA, PSO algorithm has less variables to adjust and is easy to achieve, so it is widely used in engineering. This paper focus on the comparation on several PSO algorithm and introduce a kind...
This paper develops an opposition-based learning harmony search algorithm with mutation (OLHS-M) for solving global continuous optimization problems. The proposed method is different from the original harmony search (HS) in three aspects. Firstly, opposition-based learning technique is incorporated to the process of improvisation to enlarge the algorithm search space. Then, a new modified mutation...
Most of the metaheuristic algorithms for the no-wait flowshop scheduling problem with makespan criterion have adopted the O(n2) size insertion neighborhoods, and higher order (polynomial size) neighborhoods are seldom tried. However, higher order neighborhoods can improve the solution quality of metaheuristic algorithms. The paper presents a high order neighborhood with O(n4) size called nonadjacent...
Focusing on the problem of the input and output data both contain measurement noise in linear time invariant system, this paper proposes that utilizing Tikhonov regularization of total least squares to solve the ill-poseness in process of adaptive dynamic programming. By applying the presented algorithm, the designed controller is obtained through the input and output data of the system, i.e. the...
An approach with decomposition on time windows is proposed to solve resource-constrained project scheduling problem (RCPSP) in this paper. This approach is to decompose the feasible space calculated by CPM of the original problem into some subspaces, which are searched using some schedule schema. Double justification is also performed in the search to improve the results. The results of experiments...
The traditional control methods are not able to keep control performance in a high level because response speed becomes more important for industrial control. This paper presented a fast predictive control algorithm, which was easy and simple to calculate and the principle of algorithm was very clear and greatly improved the speed of response and calculation, as well as demonstrated the principles...
This paper proposes an efficient neural network (NN) controller for the tracking control of an autonomous underwater vehicles (AUV) subject to unknown vehicle dynamics and significant uncertainties. The controller is first designed based on the error dynamics by using backstepping technique. Then, the unknown dynamics and uncertainties of the vehicle are handled by introducing a NN with single-layer...
Nowadays, manufacturing enterprises consumes a significant amount of energy; consequently, it has a significant potential to reduce resource consumption. However, key performance indicators of the traditional production do not completely take into account environmental impacts like energy consumption in production planning and scheduling. Against this background, an energy-aware scheduling model for...
Unlike conventional traveling salesman problems (TSPs) for transportation, amusement park navigation using a smart phone needs both efficiency and preference for personal adaptation. In addition, a dynamic treatment for waiting time estimation and reservation ticket use should be incorporated into a minimum path finding algorithm. This study attempts to unify an optimization method and recommender...
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